Robust and Private Learning of Halfspaces

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Robust and Private Learning of Halfspaces

30 November 2020

Pasin Manurangsi

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Papers citing "Robust and Private Learning of Halfspaces"

9 / 9 papers shown

Title
Adapting to Linear Separable Subsets with Large-Margin in Differentially Private Learning Erchi Wang Yuqing Zhu Yu-Xiang Wang 17 0 0 30 May 2025
Robust and differentially private stochastic linear bandits Vasileios Charisopoulos Hossein Esfandiari Vahab Mirrokni FedML 72 1 0 23 Apr 2023
From Robustness to Privacy and Back Hilal Asi Jonathan R. Ullman Lydia Zakynthinou 83 30 0 03 Feb 2023
Robustness Implies Privacy in Statistical Estimation Samuel B. Hopkins Gautam Kamath Mahbod Majid Shyam Narayanan 102 57 0 09 Dec 2022
How to Make Your Approximation Algorithm Private: A Black-Box Differentially-Private Transformation for Tunable Approximation Algorithms of Functions with Low Sensitivity Jeremiah Blocki Elena Grigorescu Tamalika Mukherjee Samson Zhou 105 13 0 07 Oct 2022
Algorithms with More Granular Differential Privacy Guarantees Badih Ghazi Ravi Kumar Pasin Manurangsi Thomas Steinke 117 7 0 08 Sep 2022
Learning to be adversarially robust and differentially private Jamie Hayes Borja Balle M. P. Kumar FedML 52 5 0 06 Jan 2022
On robustness and local differential privacy Mengchu Li Thomas B. Berrett Yi Yu 70 26 0 03 Jan 2022
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation Gavin Brown Marco Gaboardi Adam D. Smith Jonathan R. Ullman Lydia Zakynthinou FedML 91 50 0 24 Jun 2021